Main Reference PaperFGCH- a fast and grid based clustering algorithm for hybrid data stream, Applied Intelligence, 2018 [Java/Python/R]
  • A fast data stream clustering algorithm is proposed based on a grid. It works for a hybrid data stream such as video, internet calls, and online games. In the offline clustering stage, the similarity calculation technique is proposed to calculate the distance matrix between data points. Then, a novel clustering center fast determination algorithm (CCFD), which can automatically determine the number, center, and the radius of clusters.

+ Description
  • A fast data stream clustering algorithm is proposed based on a grid. It works for a hybrid data stream such as video, internet calls, and online games. In the offline clustering stage, the similarity calculation technique is proposed to calculate the distance matrix between data points. Then, a novel clustering center fast determination algorithm (CCFD), which can automatically determine the number, center, and the radius of clusters.

  • To improve the clustering accuracy

  • Useful similarity computation to find the closest data points

+ Aim & Objectives
  • To improve the clustering accuracy

  • Useful similarity computation to find the closest data points

  • To improve the clustering accuracy, an effective distance metric is contributed.

+ Contribution
  • To improve the clustering accuracy, an effective distance metric is contributed.

  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

+ Software Tools & Technologies
  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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